Update app.py

app.py

@@ -473,10 +473,9 @@ def detect_phoneme_from_audio(audio_segment: torch.Tensor, sample_rate: int, wor
         log(f"🔧 Padding audio from {audio_segment.shape[-1]} to {target_length} samples")
         audio_segment = torch.nn.functional.pad(audio_segment, (0, target_length - audio_segment.shape[-1]))
     elif audio_segment.shape[-1] > target_length:
-        # Take the middle portion to avoid edge effects
-        start_idx = (audio_segment.shape[-1] - target_length) // 2
-        log(f"✂️  Truncating audio from {audio_segment.shape[-1]} to {target_length} samples (middle section)")
-        audio_segment = audio_segment[:, start_idx:start_idx + target_length]
+        # Don't truncate long segments - keep full audio for complex words
+        log(f"⚠️  Audio longer than target ({audio_segment.shape[-1]} > {target_length}), keeping full length")
+        log(f"    This preserves all phonemes for long words like 'sophisticated'")
     else:
         log(f"✅ Audio segment already correct length: {target_length} samples")